Latest Dell ‘1-5-10’ Series Examines the Future of Big Data Beyond the Hype

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Last week, I attended Dell’s second in a series of highly interactive discussions exploring major technology trends and their associated challenges, opportunities and implications over the next year, five years and 10 years. For the Big Data 1-5-10 event, we assembled major industry luminaries, including Holger Mueller, Constellation Research; Carl Olofson, IDC; Nik Rouda, Enterprise Strategy Group; Anurag Agrawai, Techaisle; Jack Clark, Bloomberg; Kim Krueger, Health 2.0 News; Tom Foremski, ZDNet; Rebekah Iliff, AirPR; and David Needle, eWeek.


Our roundtable, which was moderated by Susan Etlinger from Altimeter Group, also offered real-world perspective from Dell customer Ken Yale, vice president of clinical solutions at Aetna’s ActiveHealth Management along with commentary from Dell thought leaders, including Matt Wolken, vice president of information management, Dell Software; John Thompson, general manager of analytics, Dell Software; Jai Menon, vice president and chief research officer for Dell and Matt Baker, Big Data strategist for Dell’s Enterprise Solutions Group.

Big Data: Hype vs. Reality

The group first tackled Big Data “hype vs. reality,” reaching an easy consensus that “Big Data” has taken on a highly technical, jargon-laden meaning. Instead of bits and bytes tech speak, Dell’s Matt Baker reinforced the importance of focusing more on Big Data value and outcomes.

Sure, the three Vs–volume, variety and velocity–are still relevant in defining Big Data, but we also must account for a second set: Veracity, viscosity and variability. According to ActiveHealth Management’s Yale, the classic three “Vs” fueled early interest among healthcare organizations, but it’s the second set that’s proving critical in improving patient outcomes and diagnoses.

Overall, the participants saw the cloud as an equalizer for empowering companies, especially those in the SMB segment, while helping unlock access to solutions that drive innovation and business transformation. As Dell’s Menon asserted, it’s critical to get past Big Data’s hype to focus more on business intelligence and less how to set up Hadoop clusters.

As reported in eWeek, and detailed by the panelists, the challenge is finding the right set of data that will deliver useful insights. This search puts the spotlight on analytics and business intelligence. In fact, the terms Big Data and BI may become synonymous– or better yet, Big Data may fade away as organizations gain access to better analytical tools. Dell’s Thompson stated real progress will be made over the next three-to-five years, which will give analysts the capability to go to any data source, perform discovery and then easily decide if they’d like to perform different analyses.

The Move from Descriptive to Prescriptive Analytics

This idea sparked a lively exchange on using descriptive, prescriptive and predictive analytics to drive innovation and business transformation. The panel discussed moving from analytics that describe current or past circumstances to predicting future outcomes and prescribing business strategies. A central theme was the acute skills gap facing companies that can’t afford seasoned data practitioners to guide this effort.

A great example of prescriptive analytics came from ActiveHealth’s Yale, who speculated that 60 percent of physician diagnoses could be replaced eventually by data-driven advanced analytics systems, computerized advanced clinical decision support, and devices for delivering healthcare diagnoses. While this met with initial skepticism from panelists who felt a human connection and the ability to ask follow-up questions is essential for delivering quality healthcare, everyone agreed analytics are indispensable to the diagnostician. The same holds true in every organization striving to put their data analytics to better use.

That’s why companies need to develop additional skillsets today. Over the next five years, it will become much easier to embrace data-driven programs, as the ability to abstract complexity into software will ease adoption while ubiquitous use of analytics will yield actionable insights

Gain Insight, Protect Trust

The final part of our discussion addressed privacy and the risk and rewards of sharing vs. safeguarding customer data. Dell’s Wolken highlighted the emerging problem with the limited knowledge of what individual customers relinquish in return for ambiguous, universal and perpetual consent. Too often, data collectors aren’t sure about all the ways they might use collected data in the future, so anyone giving wholesale consent could be exposing themselves to undue risk and privacy violations.

On the other hand, there is a strong desire to use analytics for improving customer experiences, which is a strong justification for customers offering their data in the first place. It comes down to understanding issues of disclosure, ownership and fairness. The individual providing information deserves better understanding of how the personal data might be used and should retain ownership with rights to take back the data if the use case changes.

In regards to fairness, look no further than the woes following cable providers. Legions of “cord cutters” are giving up their high-priced cable TV plans because they feel taken advantage of by regional monopolies that didn’t put their customers’ needs first. My advice: take the ethical data high road, both now and in the future, to protect trust and build customer loyalty.

As you can see, we covered a lot of ground. It will be interesting to see in years to come, how much of the perspectives will be aligned with major movements of the day. Thanks to all involved! And, of course, because we talk Big Data and analytics–all day, every day–feel free to reach out to me on Twitter @alertsource or via email at [email protected] to keep the conversation going.

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